Volunteer Summary

Table

Text

sets

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sets with group and time_point (formula: sets ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.43) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 19.02 (95% CI [18.48, 19.56], t(194) = 68.87, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.35, 95% CI [-0.41, 1.11], t(194) = 0.90, p = 0.367; Std. beta = 0.17, 95% CI [-0.19, 0.52])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.20, 95% CI [-0.83, 0.42], t(194) = -0.63, p = 0.529; Std. beta = -0.10, 95% CI [-0.39, 0.20])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.37, 95% CI [-0.57, 1.32], t(194) = 0.77, p = 0.440; Std. beta = 0.18, 95% CI [-0.27, 0.63])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

setv

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict setv with group and time_point (formula: setv ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.53) and the part related to the fixed effects alone (marginal R2) is of 8.36e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.03 (95% CI [10.62, 11.45], t(194) = 51.66, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.27, 95% CI [-0.32, 0.85], t(194) = 0.89, p = 0.375; Std. beta = 0.16, 95% CI [-0.20, 0.52])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.30, 95% CI [-0.14, 0.74], t(194) = 1.34, p = 0.182; Std. beta = 0.18, 95% CI [-0.09, 0.45])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.16, 95% CI [-0.83, 0.51], t(194) = -0.46, p = 0.647; Std. beta = -0.10, 95% CI [-0.50, 0.31])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

maks

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict maks with group and time_point (formula: maks ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.69) and the part related to the fixed effects alone (marginal R2) is of 7.30e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.67 (95% CI [43.72, 45.62], t(194) = 92.10, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.46, 95% CI [-0.87, 1.79], t(194) = 0.68, p = 0.498; Std. beta = 0.12, 95% CI [-0.24, 0.49])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.25, 95% CI [-1.07, 0.57], t(194) = -0.61, p = 0.543; Std. beta = -0.07, 95% CI [-0.29, 0.15])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.33, 95% CI [-0.93, 1.59], t(194) = 0.51, p = 0.607; Std. beta = 0.09, 95% CI [-0.25, 0.43])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ibs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ibs with group and time_point (formula: ibs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.71) and the part related to the fixed effects alone (marginal R2) is of 9.02e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.41 (95% CI [14.81, 16.02], t(194) = 49.84, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.03, 95% CI [-0.88, 0.82], t(194) = -0.07, p = 0.944; Std. beta = -0.01, 95% CI [-0.38, 0.35])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.13, 95% CI [-0.38, 0.63], t(194) = 0.50, p = 0.618; Std. beta = 0.06, 95% CI [-0.16, 0.27])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.50, 95% CI [-0.27, 1.28], t(194) = 1.27, p = 0.203; Std. beta = 0.22, 95% CI [-0.12, 0.55])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_e

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_e with group and time_point (formula: ers_e ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.14 (95% CI [11.77, 12.51], t(194) = 64.36, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.15, 95% CI [-0.37, 0.66], t(194) = 0.55, p = 0.583; Std. beta = 0.10, 95% CI [-0.26, 0.46])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.30, 95% CI [-0.66, 0.06], t(194) = -1.64, p = 0.101; Std. beta = -0.21, 95% CI [-0.46, 0.04])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.43, 95% CI [-0.12, 0.98], t(194) = 1.53, p = 0.126; Std. beta = 0.30, 95% CI [-0.08, 0.68])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_r

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_r with group and time_point (formula: ers_r ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.37) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.02 (95% CI [10.64, 11.39], t(194) = 57.40, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.20, 95% CI [-0.33, 0.73], t(194) = 0.74, p = 0.459; Std. beta = 0.14, 95% CI [-0.22, 0.50])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.10, 95% CI [-0.36, 0.55], t(194) = 0.41, p = 0.679; Std. beta = 0.07, 95% CI [-0.25, 0.38])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.18, 95% CI [-0.51, 0.86], t(194) = 0.50, p = 0.616; Std. beta = 0.12, 95% CI [-0.35, 0.59])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_pa

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_pa with group and time_point (formula: pss_pa ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.49) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.47 (95% CI [43.33, 45.60], t(194) = 76.54, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.50, 95% CI [-1.10, 2.10], t(194) = 0.62, p = 0.538; Std. beta = 0.11, 95% CI [-0.25, 0.47])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.95, 95% CI [-2.19, 0.29], t(194) = -1.50, p = 0.133; Std. beta = -0.21, 95% CI [-0.49, 0.07])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.36, 95% CI [-1.53, 2.24], t(194) = 0.37, p = 0.710; Std. beta = 0.08, 95% CI [-0.34, 0.51])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_ps

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_ps with group and time_point (formula: pss_ps ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.64) and the part related to the fixed effects alone (marginal R2) is of 6.84e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 26.67 (95% CI [24.63, 28.72], t(194) = 25.56, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.41, 95% CI [-3.27, 2.46], t(194) = -0.28, p = 0.782; Std. beta = -0.05, 95% CI [-0.42, 0.32])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.94, 95% CI [-0.94, 2.81], t(194) = 0.98, p = 0.328; Std. beta = 0.12, 95% CI [-0.12, 0.36])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.55, 95% CI [-4.43, 1.32], t(194) = -1.06, p = 0.289; Std. beta = -0.20, 95% CI [-0.57, 0.17])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss with group and time_point (formula: pss ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.65) and the part related to the fixed effects alone (marginal R2) is of 9.53e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 45.21 (95% CI [42.29, 48.12], t(194) = 30.39, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.91, 95% CI [-5.00, 3.18], t(194) = -0.43, p = 0.664; Std. beta = -0.08, 95% CI [-0.44, 0.28])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 1.90, 95% CI [-0.75, 4.56], t(194) = 1.40, p = 0.160; Std. beta = 0.17, 95% CI [-0.07, 0.41])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.82, 95% CI [-5.89, 2.25], t(194) = -0.88, p = 0.381; Std. beta = -0.16, 95% CI [-0.52, 0.20])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_responsible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_responsible with group and time_point (formula: rki_responsible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 3.40e-04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.95 (95% CI [19.89, 22.00], t(194) = 38.97, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.17, 95% CI [-1.31, 1.65], t(194) = 0.22, p = 0.823; Std. beta = 0.04, 95% CI [-0.33, 0.41])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.13, 95% CI [-0.89, 1.15], t(194) = 0.26, p = 0.797; Std. beta = 0.03, 95% CI [-0.22, 0.29])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.11, 95% CI [-1.67, 1.44], t(194) = -0.14, p = 0.885; Std. beta = -0.03, 95% CI [-0.42, 0.36])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_nonlinear

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_nonlinear with group and time_point (formula: rki_nonlinear ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.58) and the part related to the fixed effects alone (marginal R2) is of 9.82e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.12 (95% CI [12.39, 13.85], t(194) = 35.39, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.28, 95% CI [-0.74, 1.30], t(194) = 0.54, p = 0.591; Std. beta = 0.10, 95% CI [-0.26, 0.46])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.24, 95% CI [-0.96, 0.49], t(194) = -0.64, p = 0.522; Std. beta = -0.08, 95% CI [-0.34, 0.17])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.54, 95% CI [-0.56, 1.64], t(194) = 0.96, p = 0.337; Std. beta = 0.19, 95% CI [-0.20, 0.59])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_peer

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_peer with group and time_point (formula: rki_peer ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.56) and the part related to the fixed effects alone (marginal R2) is of 2.73e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.47 (95% CI [19.90, 21.03], t(194) = 71.17, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.17, 95% CI [-0.62, 0.96], t(194) = 0.42, p = 0.677; Std. beta = 0.08, 95% CI [-0.29, 0.44])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.08, 95% CI [-0.49, 0.65], t(194) = 0.29, p = 0.775; Std. beta = 0.04, 95% CI [-0.22, 0.30])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.08, 95% CI [-0.78, 0.95], t(194) = 0.19, p = 0.848; Std. beta = 0.04, 95% CI [-0.36, 0.44])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_expect

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_expect with group and time_point (formula: rki_expect ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.41) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 4.60 (95% CI [4.34, 4.87], t(194) = 34.19, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.30, 95% CI [-0.07, 0.67], t(194) = 1.57, p = 0.116; Std. beta = 0.29, 95% CI [-0.07, 0.65])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.12, 95% CI [-0.19, 0.43], t(194) = 0.76, p = 0.448; Std. beta = 0.12, 95% CI [-0.19, 0.42])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.10, 95% CI [-0.38, 0.57], t(194) = 0.40, p = 0.687; Std. beta = 0.09, 95% CI [-0.36, 0.55])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki with group and time_point (formula: rki ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 59.14 (95% CI [57.59, 60.69], t(194) = 74.75, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.91, 95% CI [-1.26, 3.09], t(194) = 0.82, p = 0.411; Std. beta = 0.15, 95% CI [-0.21, 0.52])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.11, 95% CI [-1.39, 1.62], t(194) = 0.15, p = 0.884; Std. beta = 0.02, 95% CI [-0.24, 0.27])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.62, 95% CI [-1.68, 2.92], t(194) = 0.53, p = 0.597; Std. beta = 0.11, 95% CI [-0.28, 0.50])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_possible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_possible with group and time_point (formula: raq_possible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.51) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.74 (95% CI [15.29, 16.20], t(194) = 67.77, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.21, 95% CI [-0.85, 0.43], t(194) = -0.64, p = 0.523; Std. beta = -0.12, 95% CI [-0.48, 0.24])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.38, 95% CI [-0.87, 0.11], t(194) = -1.53, p = 0.127; Std. beta = -0.21, 95% CI [-0.49, 0.06])
• The interaction effect of time point [2nd] on group [treatment] is statistically significant and positive (beta = 0.86, 95% CI [0.12, 1.61], t(194) = 2.28, p = 0.023; Std. beta = 0.49, 95% CI [0.07, 0.91])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_difficulty

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_difficulty with group and time_point (formula: raq_difficulty ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.55) and the part related to the fixed effects alone (marginal R2) is of 4.92e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.53 (95% CI [12.18, 12.88], t(194) = 70.28, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.23, 95% CI [-0.72, 0.26], t(194) = -0.94, p = 0.349; Std. beta = -0.17, 95% CI [-0.54, 0.19])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.15, 95% CI [-0.51, 0.20], t(194) = -0.84, p = 0.401; Std. beta = -0.11, 95% CI [-0.38, 0.15])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.33, 95% CI [-0.21, 0.88], t(194) = 1.19, p = 0.232; Std. beta = 0.25, 95% CI [-0.16, 0.65])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq with group and time_point (formula: raq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.59) and the part related to the fixed effects alone (marginal R2) is of 9.60e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 28.28 (95% CI [27.54, 29.02], t(194) = 74.87, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.44, 95% CI [-1.48, 0.60], t(194) = -0.84, p = 0.403; Std. beta = -0.15, 95% CI [-0.52, 0.21])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.49, 95% CI [-1.21, 0.23], t(194) = -1.33, p = 0.183; Std. beta = -0.17, 95% CI [-0.42, 0.08])
• The interaction effect of time point [2nd] on group [treatment] is statistically significant and positive (beta = 1.16, 95% CI [0.05, 2.26], t(194) = 2.05, p = 0.040; Std. beta = 0.40, 95% CI [0.02, 0.79])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

who

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict who with group and time_point (formula: who ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.69) and the part related to the fixed effects alone (marginal R2) is of 4.83e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.62 (95% CI [13.50, 15.75], t(194) = 25.48, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.18, 95% CI [-1.40, 1.76], t(194) = 0.22, p = 0.824; Std. beta = 0.04, 95% CI [-0.32, 0.40])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.11, 95% CI [-1.07, 0.86], t(194) = -0.22, p = 0.828; Std. beta = -0.02, 95% CI [-0.25, 0.20])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.72, 95% CI [-0.77, 2.20], t(194) = 0.95, p = 0.343; Std. beta = 0.17, 95% CI [-0.18, 0.51])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

phq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict phq with group and time_point (formula: phq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.79) and the part related to the fixed effects alone (marginal R2) is of 1.69e-04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.66 (95% CI [2.71, 4.60], t(194) = 7.55, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.09, 95% CI [-1.24, 1.43], t(194) = 0.14, p = 0.889; Std. beta = 0.03, 95% CI [-0.34, 0.39])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.12, 95% CI [-0.55, 0.79], t(194) = 0.36, p = 0.722; Std. beta = 0.03, 95% CI [-0.15, 0.21])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.13, 95% CI [-1.16, 0.90], t(194) = -0.25, p = 0.805; Std. beta = -0.04, 95% CI [-0.31, 0.24])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

gad

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict gad with group and time_point (formula: gad ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.71) and the part related to the fixed effects alone (marginal R2) is of 1.58e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.38 (95% CI [2.49, 4.27], t(194) = 7.41, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.33, 95% CI [-1.58, 0.92], t(194) = -0.52, p = 0.607; Std. beta = -0.09, 95% CI [-0.45, 0.26])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.18, 95% CI [-0.92, 0.56], t(194) = -0.48, p = 0.630; Std. beta = -0.05, 95% CI [-0.26, 0.16])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.20, 95% CI [-0.94, 1.33], t(194) = 0.34, p = 0.735; Std. beta = 0.06, 95% CI [-0.27, 0.38])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_pcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_pcs with group and time_point (formula: nb_pcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.71) and the part related to the fixed effects alone (marginal R2) is of 2.96e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 51.88 (95% CI [50.09, 53.67], t(194) = 56.89, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.50, 95% CI [-3.00, 2.01], t(194) = -0.39, p = 0.697; Std. beta = -0.07, 95% CI [-0.43, 0.29])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.80, 95% CI [-2.29, 0.69], t(194) = -1.05, p = 0.294; Std. beta = -0.11, 95% CI [-0.33, 0.10])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 1.51, 95% CI [-0.78, 3.80], t(194) = 1.29, p = 0.196; Std. beta = 0.22, 95% CI [-0.11, 0.54])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_mcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_mcs with group and time_point (formula: nb_mcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.59) and the part related to the fixed effects alone (marginal R2) is of 2.58e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 50.20 (95% CI [48.04, 52.37], t(194) = 45.51, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.37, 95% CI [-2.66, 3.40], t(194) = 0.24, p = 0.811; Std. beta = 0.04, 95% CI [-0.32, 0.41])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 1.12, 95% CI [-1.00, 3.24], t(194) = 1.04, p = 0.300; Std. beta = 0.13, 95% CI [-0.12, 0.39])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.73, 95% CI [-3.96, 2.51], t(194) = -0.44, p = 0.659; Std. beta = -0.09, 95% CI [-0.48, 0.30])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

Table